Artificial intelligence in drug discovery and development
Year: 2025
Type: article
Abstract: Artificial Intelligence (AI) has emerged as a transformative force in drug discovery and development, addressing challenges such as high costs, lengthy timelines, and frequent failures in pharmaceutical research. AI-driven approaches, including machine learning, deep learning, and bioinformatics, are revolutionizing various stages of the drug development process—from target identification and lead optimization to clinical trials and regulatory approval. AI enhances drug bioactivity prediction, facilitates personalized medicine, and streamlines clinical trial recruitment, improving efficiency and accuracy. Leading pharmaceutical companies are integrating AI to accelerate innovation and optimize therapeutic outcomes. Despite its vast potential, AI in drug discovery faces challenges such as data privacy, algorithmic bias, and regulatory hurdles. This review explores AI's applications, benefits, limitations, and future prospects in pharmaceutical research, highlighting its role in reshaping modern medicine.
Author: Shubham Gurule*, Pratik Bhabad, Anuja Darade, Sahil Gawade, Rutuja Avhad, Sakshi Bhoye
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6949411305
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